Optical navigation for Lunar landing based on Convolutional Neural Network crater detector

S Silvestrini, M Piccinin, G Zanotti, A Brandonisio… - Aerospace Science and …, 2022 - Elsevier
Traditional vision-based navigation algorithms are highly affected from non-nominal
conditions, which comprise illumination conditions and environmental uncertainties. Thanks …

Automated crater detection algorithms from a machine learning perspective in the convolutional neural network era

DM DeLatte, ST Crites, N Guttenberg, T Yairi - Advances in Space …, 2019 - Elsevier
Abstract Convolutional Neural Networks (CNN) offer promising opportunities to
automatically glean scientifically relevant information directly from annotated images …

Transfer learning for real-time crater detection on asteroids using a Fully Convolutional Neural Network

F Latorre, D Spiller, ST Sasidharan, S Basheer, F Curti - Icarus, 2023 - Elsevier
This paper proposes the use of Transfer Learning from the Moon to Ceres for real-time
autonomous crater detection operations on asteroids. This approach, based on the use of a …

Impact crater recognition methods: A review

D Chen, F Hu, L Zhang, Y Wu, J Du… - Science China Earth …, 2024 - Springer
Impact craters are formed due to the high-speed collisions between small to medium-sized
celestial bodies. Impact is the most significant driving force in the evolution of celestial …

Research progress of lunar impact crater detection

Y Jia, L Liu, G Wan, C Zhang - 2020 international conference on …, 2020 - ieeexplore.ieee.org
Impact craters are the most prominent topographic feature on the lunar surface, which will
play a very important role in the construction of lunar bases and lunar surface activities in the …

Deep domain adaptation for detecting bomb craters in aerial images

M Geiger, D Martin, N Kühl - arXiv preprint arXiv:2209.11299, 2022 - arxiv.org
The aftermath of air raids can still be seen for decades after the devastating events.
Unexploded ordnance (UXO) is an immense danger to human life and the environment …

LCDNet: An Innovative Neural Network for Enhanced Lunar Crater Detection Using DEM Data

D Miao, J Yan, Z Tu, JP Barriot - IEEE Journal of Selected …, 2024 - ieeexplore.ieee.org
Lunar craters are essential for spacecraft landing navigation and lunar exploration missions.
Deep learning holds great promise in the crater detection task, but still faces some …

Новые задачи морфометрии рельефа и автоматизированные морфологические классификации в геоморфологии

СВ Харченко - Геоморфология и палеогеография, 2020 - geomorphology.igras.ru
Аннотация Несмотря на бурное развитие вычислительных технологий и методов, рост
числа статей с применением морфометрического анализа рельефа, в этой ветви …

Boosting Crater Detection via ViT-Based Feature Fusion from near-IR Images and DEMs

Y Dai, C Xue, A Du - IEEE Geoscience and Remote Sensing …, 2023 - ieeexplore.ieee.org
Inspired by the recent progress of multimodal fusion in a variety of computer vision tasks, this
letter aims to propose a two-stream fusion crater detection network (TFCDNet). Toward this …

基于卷积神经网络的月球南极⁃ 艾特肯盆地撞击坑自动识别及中型撞击坑绝对模式年龄估算

崔兴立, 丁忞, 王冠 - 南京大学学报(自然科学版), 2021 - jns.nju.edu.cn
摘要月球南极⁃ 艾特肯盆地是太阳系最大的撞击盆地之一, 也是月球上最大, 最古老的撞击盆地.
南极⁃ 艾特肯盆地是研究早期大型撞击事件的重要窗口, 而小型撞击坑的识别与计数定年是研究 …